Experiential solving: Towards a unified autonomous search constraint solving approach

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Abstract

To solve many problems modeled as Constraint Satisfaction Problems there are no known efficient algorithms. The specialized literature offers a variety of solvers, which have shown good performance. Nevertheless, despite the efforts of the scientific community in developing new strategies, there is no algorithm that is the best for all possible situations. This paper analyses recent developments of Autonomous Search Constraint Solving Systems. Showing that the design of the most efficient and recent solvers is very close to the Experiential Learning Cycle from organizational psychology.

Original languageEnglish
Title of host publicationHCI International 2015 – Posters Extended Abstracts - International Conference, HCI International 2015, Proceedings
EditorsConstantine Stephanidis
PublisherSpringer Verlag
Pages573-577
Number of pages5
ISBN (Print)9783319213798
DOIs
StatePublished - 1 Jan 2015
Event17th International Conference on Human Computer Interaction, HCI 2015 - Los Angeles, United States
Duration: 2 Aug 20157 Aug 2015

Publication series

NameCommunications in Computer and Information Science
Volume528
ISSN (Print)1865-0929

Conference

Conference17th International Conference on Human Computer Interaction, HCI 2015
CountryUnited States
CityLos Angeles
Period2/08/157/08/15

Keywords

  • Autonomous search
  • Experiential learning
  • Metaheuristics
  • Problem solving

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